I am trying to create a slug(prettyurl) for each post added by the user. And use this slug to access the record in the db. The generated slugs might not be unique so I thought of adding the #rid at the end of the slug. So that the slugs will be unique and I can retrieve the record with the #rid while fetching the record. I can use this slug in the restful url's as well(after removing the # in the #rid).
So is there a way to append the rid to the slug property while inserting the record?
Or is there an auto increment field in orientdb which I can concatenate with the slug?
Or is there any other way to achieve the same result? I thought about generating a unique id from node js but this might add the overhead of creating and managing unique filed across multiple servers.
I am using
orientjs version: 2.1.0
orientdb version 2.1.6
Slug thing what you have explained I can not understand.
However #rid that is the Record Identifier in OrientDB is unique and it resembles like Primary Key of our Relational Database System.
to append the #rid you can use slug.append(#rid) but at the time of INSERT, it may not work as #rid is determined after the INSERT.
You can use INSERT.. RETURN #rid read it from here
However, for the Auto Increment purpose, I would say that #rid is automatically incremented. It is decided as #clusterIDOfTheRecord:positionOfTheRecordInTheCluster.
So, autoincrement there may not be needed.
Related
In my NodeJS project, I have created a mongoose schema which I changed midway through the project. More specifically, I added the unique parameter to a field.
However, this change does not seem to reflect as I am still able to create multiple documents with the same value for the parameter which I set as unique
How to fix this issue
Mongoose enforces the unique constraint by creating an index in MongoDB with the unique option.
If you already have duplicates in the collection, that index creation will fail.
Note that you may have to call syncIndexes to update the database with the new index.
I have nearly 200 000 lines of tuples in my Pandas Dataframe. I injected that data into elastic search. Now, when I run the program It should check whether the present data already there in elastic search if not present insert into it.
I'd recommend to not worry about it and just load everything into Elasticsearch. As long as your _ids are consistent the existing documents will be overwritten instead of duplicated. So just be sure to specify an _id for each document and you are fine, the bulk helpers in the elasticsearch-py client all support you setting an _id value for each document alredy.
I have a basic express app and im getting started with db queries and i want to know how to avoid multiple db queries because i dont think its efficient the way i do it :
app.get('/:word', function(req,res){
db.create({'name': word});
console.log('the word is ' + word);
});
What i want to do is :
get the word from the url
check if it exists in the datbaase (or previously requested because if it was then it was probably added already through this basic code)
if it doesn't exist then add it and then proceed to console.log
I want to add each word to my database once only and not run the db query again and again.
Here's what im thinking :
Not so efficient way
query to check if it exists before inserting one
Good way but i dont know how to start here
Cache the word being queried and maintain cache to prevent db queries
More info edit
I'm using mongodb via mongoose
the 'word' key is already unique so i know its not creating duplicate values
i dont want to run ANY db queries if that value or that url has already been hit once
The only way to check if the word already exists is to query the database before inserting. There are libraries (and also database) that implements the findOrCreate method, but this is always just an abstraction. Behind the scenes, the database will search for an existing value before writing.
If your database is huge and queryng is not suitable, you could use a cashing system (like Redis). But this definitely depends on your logic and your data size.
Probably you can just optimize the process just adding and index to the column you want be unique (I guess it's name?).
You could also define the column name as unique. When inserting, the database will throw you an error if the document already exists. But keep in mind again that, behind the scenes, the database is queryng for an existing same value before inserting. The advantage to have an "unique" column is that the index for this column is automatically created and also from your app logic (node js) you can just call the insert method and add a little bit error handling logic.
MongoDB will create any collections you use in your app if they do not already exist.
Insert Unique Value :
Create Unique Index to your key, So that the value will be added only once. If you try to add again it will throws an error to you.
To create Unique Index,
db.collection.createIndex( { "name": 1 }, { unique: true } )
Caching :
For caching, Store your data on cache system(Like: memory-cache, redis) on first time data will be query from MongoDB and then for subsequent need of data you can use cache system.
In mongo db you can use findOneAndUpdate with optional flag upsert: true documentation
To ensure that every word appears only once you should also set unique index on that field. However rememer that unique index is case sensitive so Cat and cat are different words.
I want to bulk insert an array of data using NodeJS and RethinkDB but I don't want to insert existing records (where name & value already has a record, I don't want to dupcheck on primary key id).
[
{name:"Robert", value:"1337"},
{name:"Martin", value:"0"},
{name:"Oskar", value:"1"}
]
If any of the above values already exist, don't insert, but update "value".
My current working solution is that I loop through the array and first check if it exists using a filter, if not, i insert it. But it's very slow on 10.000 records.
I don't think we have that kind of concept in RethinkDB. I tried to read the doc more. To insert a new document, use insert, to update field, use update, to replace to a whole new document, use replace(the primary key won't change)...So I don't think it's possible in RethinkDB.
Here is some way you can make it run faster:
Create a compound index contains those two fields: name and value
Then using that index to check for existence instead of using filter
Generate your own id field, instead of letting RethinkDB generated it. Therefore, you know the primary key, and use it to look up document with get which will be very fast.
I had a similar requirement in a RethinkDB project, but in that case the primary key was being checked for duplicates, and it was also custom instead of being auto-generated.
What you could do is run an async.series or async.waterfall two-step check. First pick a single object from your array, then filter the database for the name-value pairs of your current object. If the results come up null, it is unique. If not, you have a pre-existing record with same details.
Depending on the result, you can then pass on the control to next step which will either insert the new document or update existing one. It will be simpler if you use a flag for this in async.waterfall.
In past with my PHP / Rails - MYSQL apps I've used the unique ID of a table record to keep track of a record in an html file.
So I'd keep track of how to delete a record shown like this (15 being the ID of the record):
Delete this record
So now I'm using MongoDB. I've tried the same method but the objectID ._id attribute seems to be a loooong byte string that I can't use conveniently.
What's the most sensible way of binding a link in the view to a record (for deletion, or other purposes or whatever)?
If the answer is to create a new id that's unique for each document in the collection, then what's the best way to generate those unique id's?
Thank you.
You could use a counter instead of the ObjectID
But this could create a problem when inserting a new document after you deleted a previous one.
See this blog post for more detail info on Sequential unique identifiers with Node.js and MongoDB.
Or you could use the timestamp part of the ObjectID:
objectId.getTimestamp().toString()
See the node objectid docs